Reducing Process Model Input for LLM-Based Explanations: An Exploratory Study on Behavioral Abstraction Size and Explanation Quality. Patrick van Oerle, Rob Bemthuis and Faiza Bukhsh
They used LLMs as the judge of a content produced by another LLM. So I pointed out problem of bias and asked how they mitigated that. They had different containers for each LLM and they also used different LLMs (e.g., GPT, Llama).
Unlocking Sustainable Value in the Electrical and Electronic Equipment sector: A Value Network Approach. Frank Stiksma, Luís Ferreira Pires, João Luis Rebelo Moreira, Marten van Sinderen and Wilco Engelsman
- Electronic waste is seen as garbage (as if there were no economic value on it, but it does).
- Business models of EEE actors do not clearly reflect negative effects on society and enviornment
- Soceital and environmental costs shifted to society and environment.
- There is a push from the EU to move towards a circular economy.
- Lack of case0baed understanding of vlaue netwroks in EEE sector
The study aims to develop a possible approach to supor the design of sustainable-oreinted value networks in the EEE sector.
e-value modeling language is not so adequate because they do ont explicitly address sustainable values (too focused on profit).
Important observartion:
Eco-costs incorporate sustainable values in EEE value networks.
Digital Product Passports are lever for informed decision-making in sustainable value networks.
Future work:
Balanced Circular Economy policy mix
Modeling additional lifecycle value network
Scenario analysis incorporating eco-costs and implications
Developing a value-based metho dfor modeling EEE lifecycle networks and their economic and environmental impacts
Specification of information requirements in DPP model.
Towards a Taxonomy for Enterprise Architecture Debts. Jürgen Jung and Simon Hacks
Problems:
- EA drifts - complexity and bureaucracy grow
- sort-term decisions accumlate as EA debt
- misalighment between as-is and to-be
- lacking shared vocabulary for EA debts
- hard to inventory and ocmpare debts (harder to prioritize)
-prioritization of remediation remains inconsistent
- busines-IT alignment suffers without structure
- consequences across systems, processes etc.
Research Goal: Develop two completemantary taxonomies to characterize EA debts and assess their impact that enables managers and consultants to consistently describe, compare and prioritizes aligned with strategic goals.
Taxonomy 1:
For the collaboration dimension:
- Skills: lacking capability, missing training;
- Capacity: resources are lacking;
- Policty: existing rules hamper efficient collaboration; was called regulation before;
- Documentation: missing or flawed documentation; includes architecture models, enterprise and technical documents.
He made a demonstration with a case study. This is also in the paper
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